Telepsychiatry services during <scp>COVID</scp>‐19: A <scp>cross‐sectional</scp> survey on the experiences and perspectives of young adults with <scp>first‐episode</scp> psychosis
Bibliographic record
Abstract
INTRODUCTION: Limited evidence exists on the implementation of telepsychiatry within the context of early intervention services for psychosis, the need for which has become even more relevant during the COVID-19 pandemic. To address this gap, we investigated the experiences and perspectives of young adults recovering from a first-episode psychosis (FEP) following their use of telepsychiatry services (i.e. use of video conferencing technology to deliver mental health services to patients in real time). METHODS: , 2021 with young adults recruited from a specialized program for FEP located in an urban Canadian setting. Data were analysed using descriptive statistics, exploratory (Fisher's exact test), and content analysis. RESULTS: Among 51 participants (mean age = 26.0, SD = 4.7; 56.9% female), the majority were satisfied with the service (91%, 46/51), perceived that the platform was easy to use (90%, 46/51) and felt secure in terms of confidentiality (82%, 42/51). Satisfaction was related to perceptions regarding ease of use, image quality, and employment/studying status. Several partially or totally agreed that the presence of a third party was essential to login during the first few sessions (35%, 18/51), and some needed technical support (24%, 12/51) throughout the sessions. CONCLUSIONS: This study shows that telepsychiatry is feasible and acceptable to implement for patients in the early phase of psychosis recovery. It also highlights the importance of making technical support available, especially in the first few times of using the service, and addressing patient concerns regarding confidentiality, even when using secured health technologies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".